請用此 Handle URI 來引用此文件：
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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 王泓仁(Hung-Jen Wang) | |
| dc.contributor.author | Hsiang-Yun Peng | en |
| dc.contributor.author | 彭薌芸 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:14:40Z | - |
| dc.date.available | 2021-11-05 | |
| dc.date.available | 2022-11-24T03:14:40Z | - |
| dc.date.copyright | 2021-11-05 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-14 | |
| dc.identifier.citation | Glass, A. J., Kenjegalieva, K., and Sickles, R. C. 2016. A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers. Journal of Econometrics, 190 (2), 289–300. Kelejian, H.H., Prucha, I.R., 1998. A generalized spatial two-stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbance. Journal of Real Estate Finance and Econometrics 17, 99-121. Kelejian, H.H., Prucha, I.R., 1999. A generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review, 40 (2), 509-533. Kelejian, H.H., Prucha, I.R., 2007. HAC estimation in a spatial framework. Journal of Econometrics, 140 (1), 131–154. Kumbhakar S. C., Lovell C.A.K., 2000. Stochastic Frontier Analysis. Cambridge University Press. Kumbhakar, S. C., Wang, H.-J., and Horncastle, A., 2014. A Practitioner’s Guide to Stochastic Frontier Analysis. Cambridge University Press, Cambridge, England. Lee, L.F., 2001. Generalized method of moments estimation of spatial autoregressive processes. Ohio State University, Columbus. Lee, L.F., 2003. Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances. Econometric Reviews, 22 (4), 307–335. Lee, L.F., 2007. GMM and 2SLS estimation of mixed regressive, spatial autoregressive models. Journal of Econometrics 137 (2), 489-514. Lin, X., Lee, L.F., 2010. GMM estimation of spatial autoregressive models with unknown heteroskedasticity. Journal of Econometrics 157 (1), 34-52. Liu, X., Lee, L.F., and C. R. Bollinger., 2010. An efficient GMM estimator of spatial autoregressive models. Journal of Econometrics 159 (2), 303-319. Luc Anselin, 2001. Spatial econometrics. In: Baltagi B(ed) A companion to theoretical econometrics. Blackwell, Oxford. Meeusen, W., and van Den Broeck, J., 1977. Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error. International Economic Review, 18 (2), 435. Reifschneider, D., and Stevenson, R., 1991. Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency. International Economic Review, 32 (3), 715. Tsukamoto T., 2019. A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency. Japan The World Economy 50, 66-77. Wang, H.-J., and Schimdt, P. 2002. One-step and two-step estimation of the effects of exogenous variables on technical efficiency levels. Journal of Productivity Analysis, 18, 129-44. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80736 | - |
| dc.description.abstract | 本文針對具異質變異數的隨機邊界模型 (stochastic frontier model) 考慮 了個體間產出的外溢效果及空間相依性，並利用 Lee (2007) 以及 Lin and Lee (2010) 在估計空間相依模型的方法，提出新的一般動差(G MM)估計式。在異質性方面，我們遵循經典設置，假設不效率項 服從截斷常態分配下，將截斷前的變異數作為外生變數的函數。我 們首先利用在分配假設下所形成的不效率項與外生變數之間的關係， 將模型中未知的不效率項以已知的外生變數替換，再基於此經過變 數替換的模型來建構 GMM 估計的條件式，並進一步推導出 GMM 估 計量的漸近常態分佈。利用蒙地卡羅模擬，我們衡量了不同條件式 建構出的 GMM 估計量對模型的估計表現。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:14:40Z (GMT). No. of bitstreams: 1 U0001-1410202121280900.pdf: 597700 bytes, checksum: 57e9690bc7cc3b39820a0d26588ad514 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 1 Introduction p.1 1.1 The Basic Framework of Stochastic Frontier Model p.3 1.2 The Basic Framework of Spatial Autoregressive Stochastic Frontier Model p.4 2 Model and Method p.6 2.1 The Spatial Autoregressive Stochastic Frontier Model p.6 2.2 TheGMMestimatiorofSARSFmodel p.9 2.3 Consistency and Asymptotic normality of the GMM estimator p.13 2.4 TechnicalEfficiency p.14 3 Monte Carlo Simulation p.16 4 Conclusion p.19 References p.22 | |
| dc.language.iso | en | |
| dc.subject | 一般動差估計式 | zh_TW |
| dc.subject | 隨機前緣分析 | zh_TW |
| dc.subject | 異質變異數 | zh_TW |
| dc.subject | 空間自我迴歸分析 | zh_TW |
| dc.subject | Stochastic Frontier Analysis | en |
| dc.subject | Spatial Autoregressive Analysis | en |
| dc.subject | GMM | en |
| dc.subject | Heteroskedasticity | en |
| dc.title | 具異質變數的空間相依隨機邊界模型之GMM估計式 | zh_TW |
| dc.title | GMM Estimation of Spatial Autoregressive Stochastic Frontier Model with Heteroskedastic Inefficiency | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 陳怡宜(Yi-Yi Chen) | |
| dc.contributor.oralexamcommittee | 謝志昇(Hsin-Tsai Liu),(Chih-Yang Tseng) | |
| dc.subject.keyword | 隨機前緣分析,空間自我迴歸分析,一般動差估計式,異質變異數, | zh_TW |
| dc.subject.keyword | Stochastic Frontier Analysis,Spatial Autoregressive Analysis,GMM,Heteroskedasticity, | en |
| dc.relation.page | 26 | |
| dc.identifier.doi | 10.6342/NTU202103735 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-10-15 | |
| dc.contributor.author-college | 社會科學院 | zh_TW |
| dc.contributor.author-dept | 經濟學研究所 | zh_TW |
| 顯示於系所單位： | 經濟學系 | |
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